Abstract
This study developed and tested a computer method to automatically assign subjects to aggregate work groups based on their free text work descriptions. The Double Root Extended Automated Matcher (DREAM) algorithm classifies individuals based on pairs of subjects' free text word roots in common with those of standard classification systems and several explicitly defined linkages between term roots and aggregates. DREAM effectively analyzed free text from 5887 participants in a multisite chronic obstructive pulmonary disease prevention study (Lung Health Study). For a test set of 533 cases, DREAMs classifications compared favorably with those of a four-human panel. The humans rated the accuracy of DREAM as good or better in 80% of the test cases. Automated text interpretation is a promising tool for analyzing large data sets for applications in data mining, research, and surveillance. Work descriptive information is most useful when it can link an individual to aggregate entities that have occupational health relevance. Determining the appropriate group requires considerable expertise. This article describes a new method for making such assignments using a computer algorithm to reduce dependence on the limited number of occupational health experts. In addition, computer algorithms foster consistency of assignments.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Journal of Occupational and Environmental Medicine
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
